Training future computer science teachers in the context of digitalisation based on the "History of informatics" course

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World Journal on Educational
Technology: Current Issues

Volume 13, Issue 3, (2021) 354-369

www.wj-et.eu

Training future computer science teachers in the context of
digitalisation based on the “History of informatics” course
Nurzhamal T. Oshanova*, Department of Informatics and Informatization of Education, Abai Kazakh National
Pedagogical University, 050010, 13 Dostyk Ave., Almaty, Republic of Kazakhstan, https://orcid.org/0000-0002-4579-
7901
Assel K. Bukanova, Department of Informatics and Informatization of Education, Abai Kazakh National Pedagogical
University, 050010, 13 Dostyk Ave., Almaty, Republic of Kazakhstan, https://orcid.org/0000-0002-1258-0407
Zhadyra S. Kazhiakparova, Department of Natural and Scientific Disciplines, West Kazakhstan Innovation Technology
University, 090000, 44/1 Ikhsanov Str., Uralsk, Republic of Kazakhstan, https://orcid.org/0000-0002-9897-9418
Makpal T. Salbyrova, Department of Geography, Ecology and Tourism, Abai Kazakh National Pedagogical University,
050010, 13 Dostyk Ave., Almaty, Republic of Kazakhstan, https://orcid.org/0000-0002-3688-5192
Saltanat R. Sharmukhanbet, Department of Informatics and Informatization of Education, Abai Kazakh National
Pedagogical University, 050010, 13 Dostyk Ave., Almaty, Republic of Kazakhstan, https://orcid.org/0000-0002-4857-
3831
Suggested Citation:
Oshanova, N.T., Bukanova, A.K., Kazhiakparova, Z.S., Salbyrova, M.T., Sharmukhanbet, S.R. (2021). Training future
computer science teachers in the context of digitalisation based on the “History of informatics” course. World
Journal on Educational Technology: Current Issues. 13(3), 354-369 https://doi.org/10.18844/wjet.v13i3.5919 .

Received from July 31, 2021; revised from August 15, 2021; accepted from October 05, 2021
Selection and peer review under responsibility of Prof. Dr. Servet Bayram, Yeditepe University, Turkey.
©2021 Birlesik Dunya Yenilik Arastirma ve Yayincilik Merkezi. All rights reserved.
Abstract
The relevance of the study is determined by the fact that the formation of the principles of teaching the use of information
technologies needs to be laid in the learning process. The aim is to study the working conditions of a modern computer science
teacher and to determine the main directions of their training. The method of analysis made it possible to identify the discrepancy
between the realities of the work of a computer science teacher at school and the training system at a university. The paper shows
that digitalisation of learning is determined not only by the use of certain digital products but also by the formation of a digital
learning environment. The practical significance is determined by the possibilities of a structural understanding of teaching future
computer science teachers when using a combination of information technologies with the need to use them in practice in a modern
school.

Keywords: information and communication technologies (ICT); information educational environment; pedagogical activity;
professional competence.

*
ADDRESS FOR CORRESPONDENCE: Nurzhamal T. Oshanova, Department of Informatics and Informatization of
Education, Abai Kazakh National Pedagogical University, 050010, 13 Dostyk Ave., Almaty, Republic of Kazakhstan
E-mail Address: oshanova5348@unesp.co.uk / Tel: +7 7272 91 57 68

Oshanova, N.T., Bukanova, A.K., Kazhiakparova, Z.S., Salbyrova, M.T., Sharmukhanbet, S.R. (2021). Training future computer science teachers in the
context of digitalisation based on the “History of informatics” course. World Journal on Educational Technology: Current Issues. 13(3), 354-
369 https://doi.org/10.18844/wjet.v13i3.5919 .

1.Introduction
The problem of using information and communication technologies at school is of particular interest,
because, as practice shows, today the students learn the skills of working with specific software tools.
However, in the modern world, technologies are changing so rapidly that it is not clear whether students will
need this specific knowledge and skills in real life outside of school. According to scientists, this fact
conditions the need to move to a competency-based approach (Bakhmat, 2020). For example, when teaching
how to represent certain information data for various segments of the population, then the emphasis shifts
to ways of presenting the material, and software products act as tools. The student must have a good idea
of the final goal, understand how a computer can solve various problems, and use various technical means.
The speed of informatisation of society and the spread of information and communication technologies (ICT)
implies new approaches to the organisation of the educational process, in particular, in general, educational
institutions. Information support makes it possible for a person to master large volumes of information,
thereby creating new knowledge and gradually moving to a new type of society – an information society.
Such society requires changes in the content, methods and organisational forms of educational work, which
necessitates the development of information and educational environment for a general educational
institution. This phenomenon, in turn, contributes to an increase in the efficiency and flexibility of education,
modernises it and brings it in line with international standards. For the formation of students’ skills necessary
for life in an information society, it is important to integrate digital technologies into all components of the
educational process and the competent use of ICT. That is why it is of particular importance to build an
information educational environment for a general education institution, the main functions of which for a
computer science teacher are: preparation for classes, self-education, generalisation of professional
experience, training organisation, communication with parents (Моlnar & Ryabets, 2019).
In the scientific literature, there are various terms to designate the educational environment of an
academic institution, namely, information educational environment, information space, information
environment (Abramov & Sokolov, 2017). The concept of “environment personalisation” is often used, which
presupposes a certain assignment by the subject’s consciousness of a certain part of the environment as his
I. The information space of a general educational institution is defined as an adaptation model of regional
and national information spaces, which is considered as a structured set of resources and technologies based
on common educational and technological standards (Nos, 2019). An information educational environment
is a systemically organised set of information, technical, educational and methodological support,
inextricably linked with a person as a subject of the educational process (Perminov et al., 2019; Burns et al.,
2020). The information environment is perceived as a part of the information space, the information
environment closest to the individual, the set of conditions in which his activities directly take place. It is
proposed to consider the information educational environment as a pedagogical system and its support, that
is, financial and economic, material and technical, regulatory and marketing subsystem, as well as a
management subsystem (Zinchenko, 2020).
Technically, the information educational environment is built by integrating information on traditional
and electronic media, computer and telecommunication technologies, virtual libraries, distributed
databases, academic and methodological complex and an expanded didactic apparatus. In the authors’
opinion, the concept of “information educational environment” most fully conveys its content, so we will use
this definition. Thus, the information educational environment is a system created based on modern
educational, methodological, information and technical means, which consists of functional educational
subsystems that keep records of participants in the educational process. Hence, the aim of the research is to
study the working conditions of a modern computer science teacher and, accordingly, to determine the main
directions of training in the field of ICT for students, future teachers of computer science.
2. Literature Review
The interaction of the subject with the environment is considered in three dimensions: subject-object,
subject-subject and the development of the aggregate subject (when the system of relations “subject-
environment” acts as an integral subject, while implementing the principles of development and self-

355

Oshanova, N.T., Bukanova, A.K., Kazhiakparova, Z.S., Salbyrova, M.T., Sharmukhanbet, S.R. (2021). Training future computer science teachers in the
 context of digitalisation based on the “History of informatics” course. World Journal on Educational Technology: Current Issues. 13(3), 354-
 369 https://doi.org/10.18844/wjet.v13i3.5919 .

development) (Gao, 2012). Today there is a great need for the development and implementation of the
information environment of academic institutions, which would enable students to acquire the necessary
skill sets more effectively, help teachers in organising and introducing new educational teaching methods,
and meet the needs of parents to monitor the success of their children’s education (Zhao & Qian, 2018). At
the same time, some scientists note certain inconveniences associated with the use of learning environments
and applied software tools: using ready-made learning environments, the teacher is limited to the means of
learning activities that are embedded in them, and is forced to use the arsenal of visual, lecture materials,
laboratory practicals, auxiliary materials included by the developers (Qi et al., 2009). This is inconvenient as
the teacher “adjusts” to the environment (Zhao & Wang, 2013). The practice of software development has
shown that a future teacher himself can create a software tool that is not inferior in terms of its performance
to others on the market (Ji & Shen, 2009).
 Many scientists have dealt with the problems of creating information educational environments for
educational institutions, however, main attention was paid to the creation of an information educational
environment for higher educational institutions, and the role of educational (quasi-professional) activity in
the formation of skills necessary for future computer science teachers was also insufficiently defined (Qi,
2009). Consequently, in the process of professional training of future teachers, it is necessary to develop ICT
competencies for successful professional activities, to provide the necessary knowledge in the development
of the educational information environment, and to improve or modernise its individual elements (Li et al.,
2009).
 The formation of the necessary competencies of future computer science teachers is not possible without
modelling the real situations of the future professional activity, that is, the creative nature of the quasi-
professional activity, in particular when developing and modernising both the educational information
environment and its individual elements for satisfying the requirements (Aiqun, 2018). The main goals of
creating an information educational environment are associated with providing fundamentally new
opportunities for cognitive creative human activity (Yan & Fangqin, 2019). This can be achieved through the
use of modern information and technical equipment for the main educational activities: learning,
pedagogical, research, organisational, managerial and examination activities in education (Shen & Yang,
2010).
 The advantages of the information educational environment include a “paperless” version of the school
with broad functionality, the integration of traditional and distance learning forms, mobility, the formation
of 21st-century skill set, which include the intuitive mastering of computer science and computing, electronic
devices, mobile devices (Duan & Liu, 2010). Typological signs of the information educational environment
(Wang & Xing, 2011):
 1) The educational environment of any level is a complex composite object of a systemic nature.
 2) The integrity of the educational environment is synonymous with achieving a systemic effect, which
is understood as the implementation of the comprehensive goal of teaching and upbringing at the level of
lifelong education.
 3) The educational environment functions as a certain social community that develops the totality of
human relations in the context of the broad socio-cultural and ideological adaptation of a person to the world
and vice versa.
 4) The educational environment has a wide range of modality that forms a variety of types of local
environments of different, sometimes mutually exclusive qualities.
 5) In goal-oriented planning, educational environments give a total educational effect of both positive
and negative characteristics, and the vector of value orientations is determined by the target settings of the
general content of the educational process.
 6) The educational environment acts not only as a condition but also as a means of teaching and
upbringing.

 356

7) The educational environment is a process of dialectical interaction of social, spatial and subject,
psychological and didactic components that form a coordinate system of leading conditions, influences
pedagogical goals.
8) The educational environment forms a substrate for individualised activity, a transition from an
educational situation to life.
9) The educational environment exists as a certain social community that develops the totality of human
relations in the context of a broad sociocultural worldview adaptation of a person to the world, and vice
versa (Hu & Zhang, 2012).
One of the most modern teaching methods with the active use of information technology, the
effectiveness of which has already been tested abroad, is blended learning (Teng, 2013). Due to the lack of
material and technical support and the difficulty of transitioning to modern education through the ingrained
and conservative nature of traditional textbook teaching, blended learning is rarely used in secondary and
higher educational institutions (Xu et al., 2011). It is the educational information environment of an
institution that creates conditions for the systematic use of new educational technologies, including blended
learning, flipped classroom and others (Shang et al., 2014).
According to the Clayton Christensen Institute for Disruptive Innovation, blended learning is a formal
educational program in which a student studying (Li & Lu, 2017): at least in part through online learning, with
a certain element of personal control over the time, place, path and/or pace of learning; in the classroom
during a lesson supervised by a teacher; provided that all stages along the learning path of each student
within the course or subject are connected in order to provide a blended learning experience. The rapid
development of digital technologies significantly affects the change in pedagogical approaches and principles
(Wang, 2020). Teachers should be mentors for students and generators of knowledge, constantly engage in
innovations and pedagogical experiments (Li, 2020). The teacher’s use of information and communication
technologies (ICT) is characterised by a knowledge creation approach to the teaching process (Teng, 2014).
That is, ICT should serve the teacher as a means of developing student’s skills for acquiring knowledge and
developing critical thinking.
3. Materials and Methods
A modern computer science teacher has to solve a wide range of various problems, often not directly
related to the educational process. In most schools, there is no special staff obliged to maintain computers,
printers, projectors and other technical devices, lay a local network, solve organisational issues on access to
the Internet, create and maintain an educational institution’s website, etc. It is a teacher who partially or
completely performs the above and other tasks. The leading, and often the only, ICT specialist in the school
is the computer science teacher. The range of his duties and requirements for his skills has been constantly
expanding in recent years.
According to the study design, at the first stage (2019-2020), several surveys were conducted, which made
it possible to determine the level of professional competence in teachers, the range of responsibilities for
the development of the information educational environment of general education institutions, typical
difficulties that emerged in the early years of work. The survey was performed using Google Forms, the
purpose of which was to identify the actual range of responsibilities and work characteristics of a modern
computer science teacher. Note that the invitation to take the survey was sent twice with an interval of four
months to the e-mail addresses of teachers of general education institutions. 34 respondents took part in
the survey. The low level of participation in the survey indicates the passive position of the majority of
teachers, which contradicts the requirements for the representatives of this profession.
For the next stage – the ascertaining pedagogical experiment, the experimental and control groups of
students (134 and 130 people) were determined with approximately the same distribution by the levels of
certain criteria (Table 1). The results of surveys and an assessment of the level of professional competence
development in future computer science teachers confirmed the relevance of the study and made it possible
to draw the following conclusions: the overwhelming majority of students have a low level of the studied

357

Oshanova, N.T., Bukanova, A.K., Kazhiakparova, Z.S., Salbyrova, M.T., Sharmukhanbet, S.R. (2021). Training future computer science teachers in the
 context of digitalisation based on the “History of informatics” course. World Journal on Educational Technology: Current Issues. 13(3), 354-
 369 https://doi.org/10.18844/wjet.v13i3.5919 .

phenomenon both in terms of the average indicator and in the context of individual criteria, which
significantly affects the quality of teaching practice and further professional activity.

 Table 1. Development of professional competence in future computer science teachers (results of the
 ascertaining stage of the experiment (%))
 High level Average level Low level
 Criteria
 CG EG CG EG CG EG
 Motivational 1.4 1.5 31.8 32.6 66.8 65.9
 Cognitive 1.2 1.3 16.3 16.4 82.5 82.3
 Operational and pragmatic 1.9 1.8 15.2 15.8 82.9 82.4
 Communicative 1.4 1.6 24.8 25.6 73.8 72.8
 Personality 1.6 1.7 14.8 14.9 83.6 83.4
 Averaged 1.5 1.58 20.58 21.06 77.92 77.36

 At the formative stage of the pedagogical experiment, a comparative analysis of the student’s
achievements in the control and experimental groups (the author’s developments were used in the process
of teaching) was carried out. Following the goal of the formative stage of the experiment, an experimental
test of the effectiveness of the developed model of professional competence formation in quasi-professional
activities and the developed forms and methods was carried out, in particular on the material of the course
“History of informatics”. Based on the results of the formative stage of the experiment, the effectiveness of
educational activity in the control and experimental groups was determined. In the 2019-2020 academic
year, 264 students studied the discipline “History of informatics” developed based on the proposed
methodological system. For statistical confirmation of the study, the Pearson criterion ( 2 ) will be used, the
value of which will be calculated by the formula using the classic notation:
 1 ( 1 2 − 2 1 )2
 2
 = ∑3 (1)
 1 2 =1 2 + 1 

where n1 and n2 – volumes of the first and second samples; Q11, Q12, Q13 – the number of objects of the first
sample that fell into the category of state of the studied property (in our case, to groups of students with
high, medium and low levels of formed competencies), in accordance with Q21, Q22, Q23 – the number of
objects of the second sample that fell into the category of state of the studied property (for groups of
students with high, medium and low levels of formed competencies).
 Before starting the experiment, at the ascertaining stage, we put forward the null (H0) and alternative (H1)
hypotheses:
 ‒ H0: The level of formedness of professional competence of future teachers in quasi-professional
activities has not changed significantly.
 ‒ H1: The level of formedness of the professional competence of future teachers in quasi-professional
activities has undergone significant qualitative changes.
 If the null hypothesis is confirmed in the course of the research, this will indicate insignificant quantitative
differences in the levels of professional competence of future computer science teachers in quasi-
professional activities before and after the experiment. And this, in turn, indicates the ineffectiveness of the
applied methodology. In case of confirmation of an alternative (experimental) hypothesis about significant
quantitative differences in the levels of professional competence at the beginning and the end of the
experiment, we will receive mathematical confirmation of the effectiveness of the methodology developed
 2
by the authors during the thesis research. To calculate the value of the statistic , we introduce the
designations that correspond to those used in the formula to calculate the value of the Pearson criterion and
carry out the necessary calculations. For this, we will compose an auxiliary Table 2. Substituting the values of
 2
the corresponding variables into the formula for calculating the value of the Pearson criterion, we obtain 
for each criterion of the professional competence of future computer science teachers in quasi-professional
activities.

 358

Oshanova, N.T., Bukanova, A.K., Kazhiakparova, Z.S., Salbyrova, M.T., Sharmukhanbet, S.R. (2021). Training future computer science teachers in the
 context of digitalisation based on the “History of informatics” course. World Journal on Educational Technology: Current Issues. 13(3), 354-
 369 https://doi.org/10.18844/wjet.v13i3.5919 .

 2
Table 2. Auxiliary table for calculating the value of when comparing the distributions of future teachers
 of the experimental and control groups by the levels of professional competence in quasi-professional
 activities at the beginning of the experiment
 Number of Number of teachers with Number of teachers with an Number of teachers
 Sample
 teachers a high level average level with a low level
 Motivational criterion
 EG n1=134 Q11=2 Q12=44 Q13=88
 CG n2=130 Q21=2 Q22=41 Q23=87
 Total N=264 Q11+Q21=4 Q12+Q22=85 Q13+Q23=175
 Cognitive criterion
 EG n1=134 Q11=2 Q12=22 Q13=110
 CG n2=130 Q21=2 Q22=21 Q23=107
 Total N=264 Q11+Q21=4 Q12+Q22=43 Q13+Q23=217
 Communicative criterion
 EG n1=134 Q11=2 Q12=34 Q13=98
 CG n2=130 Q21=2 Q22=32 Q23=96
 Total N=264 Q11+Q21=4 Q12+Q22=66 Q13+Q23=194
 Operational and pragmatic criterion
 EG n1=134 Q11=2 Q12=21 Q13=110
 CG n2=130 Q21=2 Q22=20 Q23=108
 Total N=264 Q11+Q21=4 Q12+Q22=41 Q13+Q23=218
 Personality criterion
 EG n1=134 Q11=2 Q12=20 Q13=112
 CG n2=130 Q21=2 Q22=19 Q23=109
 Total N=264 Q11+Q21=4 Q12+Q22=39 Q13+Q23=221

 We will determine the nature of shifts in the indicators of motivational, cognitive, communicative,
operational and pragmatic, and personality criteria for the formation of the professional competence based
on comparisons of the distributions of teachers in the experimental and control groups. According to the
indicators of these criteria after the formative experiment, the authors believe that the differences in
distributions occurred due to the degree of observance of all conditions for the implementation of the
professional competence formation model in the groups trained according to the developed element of the
methodological system. According to certain characteristics of the indicators of each criterion for the
formation of professional competence, a teacher could fall into one of three categories: a group with a low,
 2
medium, or high level of the indicators and corresponding criteria. To calculate the value of statistic , after
the experiment, we introduce the designations that correspond to those used in the formula for calculating
the value of the Pearson criterion and make the necessary calculations. For this, we will draw up an auxiliary
Table 3.
 2
Table 3. Auxiliary table for calculating the value of when comparing the distributions of teachers in the
 experimental and control groups by the levels of professional competence formedness in quasi-
 professional activities after the experiment
 Number
 Number of teachers Number of teachers with an Number of teachers
 Sample of
 with a high level average level with a low level
 teachers
 Motivational criterion
 EG n1=134 Q11=16 Q12=99 Q13=19
 CG n2=130 Q21=7 Q22=81 Q23=42
 Total N=264 Q11+Q21=23 Q12+Q22=180 Q13+Q23=61
 Cognitive criterion
 EG n1=134 Q11=13 Q12=93 Q13=28
 CG n2=130 Q21=6 Q22=75 Q23=49
 Total N=264 Q11+Q21=19 Q12+Q22=168 Q13+Q23=77
 Communicative criterion

 359

EG n1=134 Q11=16 Q12=90 Q13=28
CG n2=130 Q21=10 Q22=75 Q23=50
Total N=264 Q11+Q21=26 Q12+Q22=168 Q13+Q23=78
Operational and pragmatic criterion
EG n1=134 Q11=23 Q12=102 Q13=9
CG n2=130 Q21=13 Q22=83 Q23=34
Total N=264 Q11+Q21=4 Q12+Q22=185 Q13+Q23=43
Personality criterion
EG n1=134 Q11=17 Q12=90 Q13=27
CG n2=130 Q21=11 Q22=73 Q23=46
Total N=264 Q11+Q21=28 Q12+Q22=163 Q13+Q23=73

The analysis made it possible to identify the discrepancy between the realities of the work of a computer
science teacher at school and the training system at a university, the results of the stages described above
are presented in the next section.
4. Results and Discussion
Our anonymous survey among future teachers made it possible to determine that Computer science in
schools is often taught not by computer science teachers. Thus, a survey among the respondents revealed
that only 57% are educated teachers of Mathematics or Physics with a specialisation in Computer Science,
and 43% are representatives of other professions, in particular, a programming engineer, a Handicraft
teacher, a primary school teacher, a communication engineer, a teacher of Geography and Biology,
economist. From the authors’ standpoint, this is due to the interdisciplinary, integrative nature of the subject,
as well as the wide range of responsibilities for the creation and support of the information educational
environment of the educational institution. The overwhelming majority of representatives of other
professions are in the 36-45 age group. The distribution of respondents by age and work experience as a
computer science teacher is presented in Figure 1. All teachers with less than 3 years of experience, except
for one person, are 20-25 years old, that is, young teachers who work in their specialty. Based on the results
of the survey, it was established that all of them acquired a profession “Mathematics teacher. Specialisation:
Computer Science”.

Figure 1. Distribution of teachers taking part in the survey

Analysing the technical equipment of schools, we note that within the framework of the study, we did not
set ourselves the goal of determining how modern or outdated computer technology is. The development of
support for the information educational environment of general education schools, from our point of view,
depends primarily on the beliefs of the leadership of educational institutions and other authorities. We have
not found the dependence of the number of computers on the number of students or the type of educational

360

institution. A fragment of the survey results is shown in Table 4, which presents several educational
institutions with a comparable number of students.

Table 4. Fragment of the survey results to determine the technical equipment of the school
Availability of technical means in a
Number
computer science classroom

Students at school

Computer science

Computers in the

Video projector
administration
Computers in

The Internet

Microphone
whiteboard
Interactive
classrooms

Speakers
teachers

Printer
Type of educational institution

General education school 65 1 5 3 + + - + +
General education school 84 1 10 2 + - - + +
General education school 127 2 12 2 + + - + +
General education school 140 2 7 1 + + - + +
Educational complex 675 2 10 5 + + - - +
Lyceum 700 7 61 28 + + + - -
Gymnasium 1125 2 26 10 + + + + -
General education school 1154 3 28 12 + + - + -
Specialist school 1356 2 30 16 + + + + -

It should be noted that only one educational institution has the opportunity to use robotic toys in
computer science lessons, and 7% of teachers noted that they would like to have such an opportunity.
Analysing professional experience, we found that 25% of teachers with work experience of up to three years
have no experience in preparing students for any Olympiads, competitions, tournaments. Figure 2 shows the
experiences of all respondents in preparing students for different types of computer science competitions.

71.43% 71.43%

28.57%
21.43% 21.43%

Contests Junior Academy Olympiads Online Tournaments
of Sciences Olympiads
Figure 2. The experience of teachers in preparing students for different types of computer science
competitions

We also found that 21% of teachers do not conduct any extracurricular activities. It turned out that they
all have less than three years of work experience. All other respondents regularly hold events to increase
interest in the study of computer science and programming, to deepen the knowledge of students. Among
the answers to this question, there are the following types of extracurricular activities: computer science
circle (64%), thematic weeks on informatics (43%), an educational complex based on a computer science
classroom (43%), including safe behaviour in networks, etc. Note also that 93% of informatics teachers have

361

profiles in social media, 29% have their website, 43% have a blog, and 14% of respondents are regular users
of professional networks and forums on the relevant topic.
To identify the range of responsibilities of a computer science teacher not directly related to the
educational process, we proposed questions in the form of a grid. Based on the previous survey of teachers
and their own experience, a list of situations of use and implementation of ICT that teachers face in a general
education institution was proposed. Note that the list is incomplete since the authors have tried to include
the most typical situations. All teachers who took part in the survey, regardless of education and work
experience, advise and help colleagues. The study confirmed the hypothesis that it is the computer science
teacher who overwhelmingly performs a wide range of tasks, in particular, to create an information
educational environment for a general education institution, from solving strategic issues to servicing
technical teaching aids. Realising the importance of information infrastructure development, the
management of some educational institutions finds an opportunity to maintain a special employee. Figure 3
provides a comparative analysis of the distribution of responsibilities between a computer science teacher
and a specialist staff member since the other proposed options (“school administration”, “parents/invited
specialists” and “nobody is involved”) were rare.

Figure 3. Distribution of responsibilities for the tasks of creating and maintaining the information
educational environment of the school

In 43% of schools, the administration forms applications and submissions for the purchase of equipment
without involving computer science teachers, but in 50% of schools, this task is the teacher’s area of
responsibility. An interesting fact was that the answer options “Special employee” or “Invited persons” were
chosen by teachers of schools in which a high percentage of computers are in the administrative part of the
school (at least 33% of computers in classrooms). The frequency of choosing these answer options is not
influenced by the number of students in the school, the number of informatics teachers, the type of
educational institution. In 7.14% of schools, parents or specialists from relevant companies are involved to
maintain computers in the administrative part of the school, determine the type and equipment for
connecting computers to the network. Also, a part of teachers (up to 15%) notes that no one in their
educational institutions is involved in organising the protection of personal data in electronic form, creating
a network in an educational institution, choosing and installing software for classrooms.
Besides, the analysis showed that the range of duties that a computer science teacher performs
significantly exceeds functional duties and is not directly related to the educational process. Among the
activities that are fully or partially performed by teachers of informatics, respondents noted the following:
creation and support of the website of an educational institution; deployment of support systems for
educational activities, management of educational content, file sharing, etc. lining of a local network;

362

selection, installation and configuration of software; installation and maintenance of technical training aids,
consulting colleagues, etc. At the same time, the study made it possible to determine that only about half of
the respondents who took part in the survey are teachers of computer science by education. From the
authors’ point of view, the indicated phenomenon can be explained by the relatively short time of the
existence of “Computer science” as an academic subject and the corresponding specialisation for teachers,
as well as the outstanding integration and interdisciplinary nature of this area. After listening to the course
“History of informatics” and based on the results of pedagogical practice, we surveyed students: whether
they plan to work at school in the main specialty and the specialisation “Computer science”. Thus, 19.8% of
respondents do not plan to work as a teacher, 51.6% want to work in their main specialty and 28.6% of
respondents in the field of specialisation.
2 2
Table 5 shows the values of the criterion , calculated from the data of the experiment (Table 2) ( )
by the motivational, cognitive, communicative, operational and pragmatic, and personality criteria for the
formation of professional competence of future teachers in quasi-professional activity in accordance with
2
the tabular values of ( ). Comparison of the values of the above-mentioned components gives grounds for
the conclusion that the differences in the distributions of teachers from the experimental and control groups
by the levels of all five criteria are not statistically reliable.
2
Table 5. The value of the test statistics when comparing the distributions of future teachers from the
experimental and control groups by the levels of the professional competence formedness at the beginning
of the experiment
Statistical values of the criterion
Criteria of readiness
Sample type Output
2 2
Motivational criterion EG 0.05 5.99

The general sample of students was 264 people. Despite the positive trend, which is manifested in the
growth of indicators of the levels of educational achievements and personal complexes among students in
the experimental and control groups, the qualitative results are much higher. Thus, at a high level, the biggest
increase was found for the operational and pragmatic criterion (9.8% in the control groups and 17.2% in the
experimental and 64.2% and 76.1%, respectively, for the average level) (Figure 4). According to the
personality criterion at a high level, in the experimental groups the difference is 12.4%, and in the control
groups – 8.5% and on average 56% and 67.5%, respectively (Figure 5).

Figure 4. Results of a comparative analysis of the ascertaining and control stages of the experiment
according to the operational and pragmatic criterion

Figure 5. The results of a comparative analysis of the ascertaining and control stages of the experiment
according to the personality criterion

According to the communicative criterion at a high level in the experimental group, the difference is 11.9%
compared to 7.6% in the control (Figure 6), on average 67.2% and 54.0%, respectively. According to the
motivational criterion at a high level, the increase in the experimental groups is 11.6%, in the control – 5.6%
(Figure 7), and on average 62.0% and 74.0%, respectively.

364

Oshanova, N.T., Bukanova, A.K., Kazhiakparova, Z.S., Salbyrova, M.T., Sharmukhanbet, S.R. (2021). Training future computer science teachers in the
 context of digitalisation based on the “History of informatics” course. World Journal on Educational Technology: Current Issues. 13(3), 354-
 369 https://doi.org/10.18844/wjet.v13i3.5919 .

 Figure 6. Results of a comparative analysis of the ascertaining and control stages of the experiment
 according to the communicative criterion

 Figure 7. The results of a comparative analysis, ascertaining and control stages of the experiment according
 to the motivational criterion

 The difference in the experimental groups according to the cognitive criterion at the high level of the
criterion is 9.8%, and in the control groups – 4.6% (Figure 8), and on average 69.1% and 58.0%, respectively.

 Figure 8. The results of a comparative analysis of the ascertaining and control stages of the experiment
 according to the cognitive criterion

 365

Oshanova, N.T., Bukanova, A.K., Kazhiakparova, Z.S., Salbyrova, M.T., Sharmukhanbet, S.R. (2021). Training future computer science teachers in the
 context of digitalisation based on the “History of informatics” course. World Journal on Educational Technology: Current Issues. 13(3), 354-
 369 https://doi.org/10.18844/wjet.v13i3.5919 .

 Substituting the values of the corresponding variables into the formula for calculating the value of the
 2
Pearson criterion (Table 3), we obtain for each criterion in the Table 7.
 2
 Table 7. The value of the test statistics when comparing the distributions of future teachers from the
 experimental and control groups by the levels of the professional competence formedness after the
 experiment
 Statistical values of the criterion 
 Criteria of readiness
 Sample type Output
 EG 2 2
 Motivational criterion 13.96 5.99 > 
 CG
 EG 2 2
 Cognitive criterion 10.17 5.99 > 
 CG
 EG 2 2
 Communicative criterion 10.03 5.99 > 
 CG
 EG 2 2
 Operational and pragmatic criterion 19.2 5.99 > 
 CG
 EG 2 2
 Personality criterion 7.94 5.99 > 
 CG
 2 2
 Formedness Arithmetic mean 11.2 5.99 > 

 The results of a comparative analysis of the ascertaining and control stages of the experiment (Table 8)
showed a significant advantage of the developed methodological system of teaching by the chosen question
of the methodology of teaching computer science (according to the averaged indicators), which is shown in
Figure 9.

 Table 8. Comparison of the results of the ascertaining and control stages of the experiment (%)
 Ascertaining

 Ascertaining

 Ascertaining
 experiment

 experiment

 experiment
 Difference

 Difference

 Difference
 Formative

 Formative

 Formative
 Group

 stage

 stage

 stage
 Criteria

 EG 1.50 11.60 10.10 32.60 74.00 41.40 65.90 14.40 -51.50
 Motivational
 CG 1.40 5.60 4.20 31.80 62.00 30.20 66.80 32.40 -34.40
 EG 1.30 9.80 8.50 16.40 69.10 52.70 82.30 21.10 -61.20
 Cognitive
 CG 1.20 4.60 3.40 16.30 58.00 41.70 82.50 37.40 -45.10
 EG 1.80 17.20 15.40 15.80 76.10 60.30 82.40 6.70 -75.70
 Operational and pragmatic
 CG 1.90 9.80 7.90 15.20 64.20 49.00 82.90 26.00 -56.90
 EG 1.60 11.90 10.30 25.60 67.20 41.60 72.80 20.90 -51.90
 Communicative
 CG 1.40 7.60 6.20 24.80 54.00 29.20 73.80 38.40 -35.40
 EG 1.70 12.40 10.70 14.90 67.50 52.60 83.40 20.10 -63.30
 Personality
 CG 1.60 8.50 6.90 14.80 56.00 41.20 83.60 35.50 -48.10
 EG 1.58 12.80 11.22 21.06 73.10 52.04 77.36 14.10 -63.26
 Average
 CG 1.50 6.60 5.10 20.58 61.40 40.82 77.92 32.00 -45.92

 366

Figure 9. The results of a comparative analysis of the ascertaining stage of the experiment (according to
the average indicator)
2
Comparison of the values of the criterion =11.2, calculated from the data of the performed experiment
2
and the critical =5.99 for the significance level of 0.05 and the number of degrees of freedom 2, gives
grounds for the conclusion that the differences in the distributions of the control and experimental groups
by the levels of each criterion are statistically reliable and provide the effectiveness of the developed model
for the professional competence formation, and, therefore, there is a confirmation of the alternative
hypothesis that we put forward at the beginning of our experimental study. At a high level, the greatest
changes were observed in the experimental group according to the operational and activity criterion: the
difference was 15.40% (versus 7.90% in the control group). In our opinion, this is due to the fact that as a
result of the expansion of the content of forms and methods of professional training within the framework
of the developed course, students during quasi-professional activities could additionally develop the
acquired practical skills. The smallest increase at a high level was recorded by the cognitive criterion: 8.5% in
the experimental group and 3.4% in the control group. This is due to the practical orientation of the
developed training content and the use of the competency-based approach as a leader in the process of
organising experimental training. According to the average indicator at a high level, the difference in the
experimental groups is 11.22% and in the control groups – 5.1%. Also, a more significant increase in the
average indicator at the average level was recorded in the experimental groups, namely 52.04% (versus
40.82% in the control groups).
The results obtained confirm the reliability of the quantitative data obtained and show a positive dynamic
of growth in the levels of formation of the studied indicators, which can be considered a confirmation of the
effectiveness of the models and organisational and pedagogical conditions for the formation of professional
competence of future computer science teachers in quasi-professional activities introduced into the
methodological system of training future teachers. Based on the above, the goal of the study can be
considered achieved.

5. Conclusions
Thus, the conducted experiment of students’ achievements made it possible to record positive dynamics
in both groups (control and experimental), however, the quantitative indicators of the criteria in the
experimental group grew faster and with a greater difference against changes in the control group both for
each of the criteria and for the average indicator. The analysis of the results of the formative stage of the
pedagogical experiment confirmed the effectiveness of the developed forms, content and methods of
forming the professional competence of future informatics teachers in quasi-professional activities.

367

It is beyond argument that modern school cannot exist without integration with information and
communication technologies and building an information educational environment of the school, the integral
parts of which are the school website, electronic document management, a sufficient number of computers
connected to the Internet for organising the entire educational process, access to electronic libraries,
archives, educational video collections, educational content management systems and much more. Of
particular importance is the preparation of the future computer science teacher to work in the conditions of
rapidly changing technologies, under the influence of which new trends in education are emerging. Today, a
computer science teacher is a pioneer who independently learns and presents new opportunities to his
colleagues. In accordance with the requirements of society for the level of training of a modern teacher, the
training system in a higher education institution must also change.

Recommendations
Based on the results of the conducted investigation, the following recommendations for further research
should be identified:
1. The use of information products in the learning process is worthy of being explored more.
2. Further study may include the possibilities of a structural understanding of teaching future computer
science teachers when using a combination of information technologies with the need to use them in practice
in a modern school.

Acknowledgements
None.

References
Abramov, R. A. & Sokolov, M. S. (2017). Features of corruption in the educational sphere in the context of globalization
of educational space. Journal of Legal, Ethical and Regulatory Issues, 20(Special issue 1), 1‒10.
Aiqun, Z. H. U. (2018). An IT capability approach to informatization construction of higher education institutions.
Procedia Computer Science, 131, 683‒690. https://doi.org/10.1016/j.procs.2018.04.312
Bakhmat, N. V. (2020). Subjective properties of the future pedagogical worker in the system of professional training.
Scientific Bulletin of Mukachevo State University. Series “Pedagogy and Psychology”, 1(11), 56‒60.
Burns, E., Silvennoinen, E., Kopnov, V., Shchipanova, D., Papić-Blagojević, N. & Tomašević, S. (2020). Supporting the
development of digitally competent VET teachers in Serbia and Russia. Obrazovanie i Nauka, 22(9), 174‒203.
Duan, W. & Liu, S. (2010). A study on the evaluation model of the higher education informatization. In 2010 International
Conference on Future Information Technology and Management Engineering, FITME 2010, 1 (pp. 365‒368).
https://doi.org/10.1109/FITME.2010.5656320
Gao, D. (2012). Analysis of the research subject of education informatization based on the keyword. Wuhan Daxue
Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 37(2), 241‒244.
Hu, S. & Zhang, J. (2012). Cost-benefit factors analysis based on principal component in education informatization.
Advances in Information Sciences and Service Sciences, 4(17), 365‒372.
https://doi.org/10.4156/AISS.vol4.issue17.42
Ji, J. & Shen, Z. (2009). A study on education informatization of the community-based university education. In
Information Systems in the Changing Era: Theory and Practice – Proceedings of the 11th International Conference on
Informatics and Semiotics in Organisations, ICISO 2009 (pp. 233‒238). IEEE Press.
Li, L. & Lu, C. (2017). Comprehensive evaluation based on VEDI index measure of vocational education informatization
level. In Proceedings – 5th International Conference on Educational Innovation through Technology, EITT 2016 (pp.
159‒162). Tainan: IEEE Press. https://doi.org/10.1109/EITT.2016.38

368

Oshanova, N.T., Bukanova, A.K., Kazhiakparova, Z.S., Salbyrova, M.T., Sharmukhanbet, S.R. (2021). Training future computer science teachers in the
 context of digitalisation based on the “History of informatics” course. World Journal on Educational Technology: Current Issues. 13(3), 354-
 369 https://doi.org/10.18844/wjet.v13i3.5919 .

Li, N. (2020). Informatization teaching of optional courses of physical education in colleges and universities. Advances
 in Intelligent Systems and Computing, 1017, 1675‒1679. https://doi.org/10.1007/978-3-030-25128-4_212
Li, W., Wang, H., Wei, Y., Gao, J. & Cao, B. (2009). Grey relational evaluation on higher education informatization. In 2nd
 International Symposium on Knowledge Acquisition and Modeling (KAM) (pp. 285‒288). Wuhan: IEEE Press.
 https://doi.org/10.1109/KAM.2009.146
Mоlnar, Т. І. & Ryabets, D. V. (2019). Scientific and research work as the basis of professional training of future teachers
 of primary school. Bulletin of Mukachevo State University. Series “Pedagogy and Psychology”, 1(9), 95‒97.
Nos, L. S. (2019). Pedagogical practising in the system of professional training of future teachers: experience of Canada
 and Britain. Bulletin of Mukachevo State University. Series “Pedagogy and Psychology”, 1(9), 203‒206.
Perminov, E. A., Gadjiev, D. D. & Abdurazakov, M. M. (2019). About relevance of fundamentalisation of mathematical
 training of students of the pedagogical directions during the digital era. Obrazovanie i Nauka, 21(5), 86‒111.
Qi, B., Dong, Y., Chen, L., Qi, W. & Okawa, Y. (2009). The impact of robot instruction to education informatization. In 1st
 International Conference on Information Science and Engineering, (ICISE) (pp. 3497‒3500). Nanjing: IEEE Press.
 https://doi.org/10.1109/ICISE.2009.1216
Qi, Z. (2009). An evaluation of education informatization based on BP neural network. In 1st International Conference
 on Information Science and Engineering, (ICISE) (pp. 3215‒3218). Nanjing: IEEE Press.
 https://doi.org/10.1109/ICISE.2009.261
Shang, J., Cao, P. & Nie, H. (2014). The latest development of education informatization in North America and its
 implications. In Proceedings – 2014 International Conference of Educational Innovation Through Technology, EITT
 2014 (pp. 170‒175). Brisbane: IEEE Press. https://doi.org/10.1109/EITT.2014.35
Shen, X.-C. & Yang, H.-N. (2010). Research of training mode of informatization talent in our country. In 2010
 International Conference on E-Product E-Service and E-Entertainment, ICEEE (pp. 1‒3). Henan: IEEE Press.
 https://doi.org/10.1109/ICEEE.2010.5660144
Teng, Z. (2013). On sport informatization under the perspective of education informatization. In ACM International
 Conference Proceeding Series (pp. 205‒207). New York: Association for Computing Machinery.
 https://doi.org/10.1145/2556871.2556915
Teng, Z. (2014). On physical education teaching informatization under the perspective of education informatization.
 Journal of Chemical and Pharmaceutical Research, 6(4), 1009‒1013.
Wang, B. & Xing, H. (2011). The application of cloud computing in education informatization. In 2011 International
 Conference on Computer Science and Service System, CSSS 2011 – Proceedings (pp. 2673‒2676). Nanjing: IEEE Press.
 https://doi.org/10.1109/CSSS.2011.5973921
Wang, B. (2020). Cooperative model of the English-writing instruction in informatization education. Lecture Notes in
 Electrical Engineering, 551, 726‒732. https://doi.org/10.1007/978-981-15-3250-4_92
Xu, S.-J., Ren, X.-L. & Zhou, J. (2011). Classification and comparison of the college physics exercises based on education
 informatization. In TEIN 2011 –2011 2nd ETP/IITA Conference on Telecommunication and Information, 2, 277‒280.
Yan, B. & Fangqin, Z. (2019). Evaluation model of rural primary and middle school education informatization based on
 data sharing. In Proceedings – 2019 International Conference on Smart Grid and Electrical Automation, ICSGEA 2019
 (pp. 437‒442). Xiangtan: IEEE Press. https://doi.org/10.1109/ICSGEA.2019.00105
Zhao, W. & Wang, L. (2013). College physical education informatization development research. In Proceedings – 3rd
 International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC
 2013 (pp. 1297‒1300). Shenyang: IEEE Press. https://doi.org/10.1109/IMCCC.2013.288
Zhao, Y.-Y. & Qian, D.-M. (2018). Comparative analysis of current situation of education informatization in urban and
 weak areas in China. In ICCE 2018 – 26th International Conference on Computers in Education, Main Conference
 Proceedings (pp. 793‒795). Kenting: APSCE. Retrieved from http://icce2018.ateneo.edu/wp-
 content/uploads/2018/12/C7-15.pdf
Zinchenko, A. S. (2020). Project-focused personnel management approach of higher educational institutions. Asia Life
 Sciences, 22(2), 243‒256.

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